Top Artificial Intelligence Jobs

Leads company-wide operations across laboratory, sales, and collaboration implementation. Develops strategic plans, KPIs, and process improvements; manages operational teams; ensures regulatory, quality, and safety compliance; collaborates cross-functionally with R&D, lab operations, QA, HR, external partners, and supply chain; and reports performance insights to senior leadership.

Own the full B2B sales cycle for Lavalier, including outbound pipeline generation, account targeting, stakeholder engagement, product demonstrations, deal project management, procurement and security coordination, and closing foundational customers. Partner with marketing and leadership to shape messaging, pricing, go-to-market strategy, and sales processes. Provide structured product feedback and help establish the company’s early sales motion.

Owns customer research projects end to end, from scoping and contributor orchestration through quality assessment and dataset delivery. Recruits and manages expert contributors, tracks shifting milestones, evaluates output quality, and ensures deliverables meet researchers’ standards. This hands-on role combines project operations, strategic decision-making, product management, stakeholder coordination, and customer partnership in a fast-moving frontier AI environment.

Drive regional business growth by identifying and prospecting insurance brokers, building relationships, presenting computer vision solutions, developing sales plans, achieving targets, and expanding market share. Partner with underwriters and internal teams to generate revenue, support implementation, tailor proposals, and maintain stakeholder relationships. The role focuses on workers’ compensation and requires frequent travel throughout the Northeastern region.

Senior Business Analyst responsible for gathering and clarifying requirements, facilitating workshops, managing stakeholders, optimizing workflows, and aligning solutions with business goals. The role focuses on customer-centric process improvement, automation, regulatory compliance, risk mitigation, and banking operations. Candidates should have extensive Pega Smart Dispute and banking experience, familiarity with BPM tools, and experience delivering solutions using Agile or Scrum methodologies.

Build and lead Rerun’s physical AI community and events program. Responsibilities include mapping relevant robotics communities, designing developer events and recurring programs, partnering with engineering and founders on technical content, representing the company at conferences and meetups, and coordinating with teams in Sweden and San Francisco. The role combines field marketing, developer evangelism, community building, and hands-on event execution.

Build scalable backend services, APIs, workflow orchestration, integrations, and AI agent infrastructure for enterprise procurement, invoicing, contracts, and payments. Develop agent runtimes, multi-agent coordination, observability, evaluation, and testing systems. Ensure reliability, security, compliance, auditability, performance, and fault tolerance across distributed systems handling sensitive financial and operational data.

Own the full post-sale lifecycle for North American accounts, including onboarding, adoption, renewals, expansion, forecasting, and customer value realization. Identify and close growth opportunities, negotiate renewals, gather product feedback, and keep customers engaged with the platform. As the first local Account Manager, help establish the regional account-management playbook, support future hires, visit strategic customers, and represent the company at trade shows and industry events.

Own the full B2B sales cycle for SaferFleet’s emerging fleet safety and risk intelligence business. Prospect commercial fleet customers, conduct discovery, demonstrate solutions, build partnerships, close deals, and transition customers. Develop expertise in fleet safety, telematics, MVR monitoring, compliance, insurance, and claims while providing customer feedback to shape product, pricing, messaging, and go-to-market strategy.

Build and maintain production backend systems for a real-time learning AI engine: APIs, data pipelines, performance optimization, testing, CI/CD, and troubleshooting. Collaborate with AI researchers, prototype features, and operate LLM instances (Claude) at scale.